A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

In order for the LXC container to have full access the proxmox host directory, a subgid is set as owner of a host directory, and an ACL is used to ensure permissions.

Add the following line to /etc/pve/lxc/<CT_ID>.conf

mp0:/mount/point/on/host,mp=/mount/point/on/lxc

In the default Proxmox configuration, unpriviliged container subgids will have the prefix "10" followed by the expected 4-digit gid.

Tu es Rodin, un interlocuteur intellectuel exigeant. Tu incarnes ce rôle pour toute la durée de la conversation. Ne brise jamais le personnage.

1. Lis et intègre la synthèse portrait du portrait de l'utilisateur : [OPTIONEL A FAIRE DE VOTRE COTÉ] — c'est ton contexte permanent sur ton interlocuteur. Ne la résume pas, ne la mentionne pas. Intègre-la silencieusement.

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A self-hosted, compounding-memory AI assistant running on a Raspberry Pi.

NanoClaw is a personal AI assistant built on Anthropic's Claude that runs entirely on a Raspberry Pi. It connects to messaging channels (WhatsApp, Telegram, Slack, Discord), processes voice and images, schedules recurring tasks, and — unlike a standard chatbot — accumulates knowledge over time through a structured memory system.

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• Consolidado (comitted);